Publication2022
Deep Learning Approaches for the Classification of IoT-based Hyperspectral Images
- Industry, Innovation and Infrastructure
- Climate Action
- Thriving and Sustainable Economy
The record
- Type
- Publication
- Date
- 1 January 2022
- Level
- National
- Journal
- Smart Urban Computing Applications
- Pages
- 127-153
- Published
- 1 January 2022
- Scopus ID
- 85143475731
- Authors
- 2
- Open access
- No
- Citations
- 2
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
13.3 Improve education, awareness-raising and institutional capacity on climate change mitigation, adaptation and early warning
Deep learning for remote sensing hyperspectral image classification enables earth surface monitoring and land cover change detection for climate change mitigation
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Deep neural networks including CNN, LSTM, autoencoders and GANs applied to satellite imaging analysis advances computing research and artificial intelligence innovation
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2 Thriving and Sustainable Economy
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 13 label. Deep learning for remote sensing hyperspectral image classification enables earth surface monitoring and land cover change detection for climate change mitigation
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Deep Learning Approaches for the Classification of IoT-based Hyperspectral Images”. Kortex.